Abstract
Turing’s neural-network-like structures (unorganized machines) are presented and compared to Kauffman’s random boolean networks (RBN). A self-organizing topology evolving algorithm is applied to Turing’s networks and it is shown that the network evolves towards an average connectivity of KC = 2 for large systems (N →∞).
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CITATION STYLE
APA
Teuscher, C., & Sanchez, E. (2001). Self-organizing topology evolution of turing neural networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2130, pp. 820–826). Springer Verlag. https://doi.org/10.1007/3-540-44668-0_114
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